Saurav Jha – Email: saurav [dot] jha [at] unsw [dot] edu [dot] au

I am a first year PhD student at UNSW Sydney jointly supervised by Dr. Lina Yao and Dr. Dong Gong. Prior to joining UNSW, I was a research assistant at the Computer Vision Center, Barcelona where I worked with Dr. Joost van de Weijer on continual learning. I completed my Erasmus Mundus Joint Master's Degree in Advanced Systems Dependability from the University of St Andrews, UK, and the University of Lorraine, France. During my master's, I interned with the MULTISPEECH group at Inria Nancy where I worked with Dr. Emmanuel Vincent on training domain-specific language models for Automatic Speech Recognition. Before my master's and right after my undergrad, I worked as a machine learning engineer at FactSet Research Systems Inc.

I earned my BS in Computer Science and Engineering from MNNIT Allahabad, India. While there, I also interned at the Natural Language Processing Research lab at the Indian Institute of Technology (IIT-BHU). I grew up dreaming of quasi-stellar objects and witnessing first-generation post-monarchic changes in Nepal. I enjoy running, traveling, chatting, and movies in my free time. I am readily reachable via any media mentioned on this website.

2022

September: Pre-print for my work surveying the Neural Process Family is up and can be found at this https url.
June: My first co-authored paper, “Towards Exemplar-Free Continual Learning in Vision Transformers“, receives the Matrix-sponsored best runner-up award at CVPR 2022 workshop on continual learning (CLVision)!
June: I am tutoring the UNSW Business school courses INFS3830 and INFS5730 on social media analytics.
April: My first co-authored paper “Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization” has been accepted by the CLVision workshop to appear in the CVPR 2022 proceedings!
February: I have moved to Sydney to start my PhD at the School of Computer Science, UNSW Sydney.

2021

November: I have been awarded the University International Postgraduate Award (UIPA) for my PhD studies at UNSW Sydney.
October: My blog post summarizing my Erasmus Mundus master’s experience has been selected to be published on Erasmus Mundus Association’s website. The link can be found here.
July: My thesis is awarded the best Master’s thesis presentation (out of 46 students) at the 2021 DEPEND summer school. My thesis report is available here.
June: I have won the 1000€ prize for the best student poster (“Towards Better Voice Assistants”) at the Digital Ethics4EU workshop “Digital Ethics: can we do better?”
April: Our paper “Continual Learning in Sensor-based Human Activity Recognition: an Empirical Benchmark Analysis“ is accepted by Information Sciences.
March: I have started my internship in the MULTISPEECH team at Inria Nancy working on the H2020 Comprise project.

01 January: I did a 14 kms. hike to Mer de Glace from Chamonix Mont Blanc – my first visit to a glacier ever. Here is a still from the day:

2020

November: My co-authored paper “Continual Activity Recognition with Generative Adversarial Networks” gets accepted to be issued in the ACM Transactions on Internet of Things.
October: Hosted a webinar on EMJMD application processes in collaboration with Erasmus Mundus, Nepal.
September: My blog post “Continual Learning – where are we?” is up in Towards Data Science.
July: One paper accepted at the Workshop on Continual Learning, ICML 2020.
April: Appointed as the program representative to the EMA for the Erasmus Mundus DEPEND 2020/21 course.
March: Our team won the Barclays chatbot challenge at Hack the Burgh 2020, the University of Edinburgh. The project description is available here.

2019

September: I have moved to St Andrews, Scotland to kick off my Erasmus Mundus master’s journey.
April: I have been awarded the prestigious Erasmus Mundus scholarship for a two-year Master’s study at the University of St Andrews, UK and the Universite de Lorraine, France.

2018

June: I have joined the Cognitive Computing team at FactSet Research Systems as a Machine Learning Software Engineer.